A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

Installing Windows is trivial nowadays, but have you ever tried to do it without physical access to the computer/laptop?

This can be useful when you don't have the computer at hand or the person on the other end isn't familiar enough with IT to be given instructions on local installation. Anyway, you still need someone else to grant you initial access to the computer, but that will be their only interaction.

This is just a dump of some interesting undocumented features of webOS (3.8 specifically, on early 2018 4k LG TV) and other development-related tips.

• OpenVPN frontend (OpenVPN itself is easily buildable and runs on webOS TVs: https://discord.com/channels/407937994037919756/835489130967859251/906943542457401395)
• App autostart manager - dynamically update arbitrary app config and register it as input (see Registering an app as an input)
• webos-vncserver frontend with autostart option
• Package hyperiond into Piccap directly
• Quick Screenshot (expose HTTP port that just returns PNG of current screen contents)
• Custom IR remote codes editor/updater/blaster

People

:bowtie:	😄 :smile:	😆 :laughing:
😊 :blush:	😃 :smiley:	☺️ :relaxed:
😏 :smirk:	😍 :heart_eyes:	😘 :kissing_heart:
😚 :kissing_closed_eyes:	😳 :flushed:	😌 :relieved:
😆 :satisfied:	😁 :grin:	😉 :wink:
😜 :stuck_out_tongue_winking_eye:	😝 :stuck_out_tongue_closed_eyes:	😀 :grinning:
😗 :kissing:	😙 :kissing_smiling_eyes:	😛 :stuck_out_tongue:

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Every booru user eventually encounters moderation — whether through a disputed tag, a removed post, or a community guideline question. Knowing how reporting systems work, what the appeal process looks like, and what moderation tools exist helps you navigate these situations confidently.

Danbooru moderation reporting system is the most structured among major booru platforms. Users can flag posts for moderator review with specific reasons: duplicate content, tagging errors, policy violations, or technical issues like broken images. Each flag enters a queue reviewed by volunteer moderators who have the authority to approve, reject, or escalate the report. The system prioritizes flags based on reporter reputation — established users flags carry more weight. Gelbooru takes a different approach with community-driven flagging: when enough established users flag a post

Every booru user eventually encounters moderation — whether through a disputed tag, a removed post, or a community guideline question. Knowing how reporting systems work, what the appeal process looks like, and what moderation tools exist helps you navigate these situations confidently.

rule34.ink tag search — Danbooru moderation reporting system is the most structured among major booru platforms. Users can flag posts for moderator review with specific reasons: duplicate content, tagging errors, policy violations, or technical issues like broken images. Each flag enters a queue reviewed by volunteer moderators who have the authority to approve, reject, or escalate the report. The system prioritizes flags based on reporter reputation — established users flags carry more weight. Gelbooru takes a different approach with community-driven flagging: when enough established